Scientists at the Massachusetts Institute of Technology (MIT) have developed a computational tool that can predict mutations to help create better proteins. The tool facilitates the creation of improved versions of proteins through strategic mutations and could offer significant advancements in neuroscience research and medical applications. One common procedure for producing improved proteins involves introducing…
Researchers at MIT have developed a computational method to hasten the process of generating optimized versions of proteins, using only a small amount of data. The researchers have generated proteins with mutations capable of improving Green Fluorescent Protein (GFP) and a protein used to deliver DNA for gene therapy from an adeno-associated virus (AAV).
The process…
Protein engineering is a complicated process, typically involving the random mutation of a natural protein with a desirable function, repeated until an optimal version of the protein is developed. This process has proven successful for proteins like the green fluorescent protein (GFP), but this isn't the case for all proteins. Researchers at MIT have developed…
MIT researchers have developed a computational approach to help predict mutations that can create optimized versions of certain proteins, working with a relatively small amount of data. The team believes the system could lead to potential medical applications and neuroscience research tools.
Usually, protein engineering begins with a natural protein that already has a desirable function,…
MIT researchers have developed a computational approach that predicts protein mutations, based on limited data, that would enhance their performance. The researchers used their model to create optimized versions of proteins derived from two naturally occurring structures. One of these was the green fluorescent protein (GFP), a molecule used to track cellular processes within the…
The MIT Stephen A. Schwarzman College of Computing recently celebrated the completion of its new Vassar Street building. The dedication ceremony was attended by members of the MIT community, distinguished guests, and supporters, reflecting on the transformative gift from Stephen A. Schwarzman that initiated the biggest change to MIT’s institutional structure in over 70 years.…
Scientists at Massachusetts Institute of Technology (MIT) have developed a computational model aimed at simplifying the process of protein engineering. The researchers applied mutations to natural proteins with desirable traits, such as the ability to emit fluorescent light, using random mutation to cultivate better versions of the protein. The technique was deployed using the green…
The number of satellites orbiting the Earth has grown exponentially in recent years, both due to lower costs and a rise in demand for services that satellites can provide, such as broadband internet and climate surveillance. However, this increase in activity also raises concerns around safety, security, and the environment, necessitating enhanced methods for monitoring…
MIT researchers have developed a technique for improving the accuracy of uncertainty estimates in machine-learning models. This is especially important in situations where these models are used for critical tasks such as diagnosing diseases from medical imaging or filtering job applications. The new method works more efficiently and is scalable enough to apply to large…
Artificial intelligence (AI) and particularly large language models (LLMs) are not as robust at performing tasks in unfamiliar scenarios as they are positioned to be, according to a study by researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL).
The researchers focused on the performance of models like GPT-4 and Claude when handling “default tasks,”…
GenSQL, a new AI tool developed by scientists at MIT, is designed to simplify the complex statistical analysis of tabular data, enabling users to readily understand and interpret their databases. To this end, users don't need to grasp what is happening behind the scenes to develop accurate insights.
The system's capabilities include making predictions, identifying anomalies,…
MIT President Sally Kornbluth and Provost Cynthia Barnhart last year issued a call for papers with the aim of developing effective strategies, policy recommendations, and calls to action in the field of generative artificial intelligence (AI). The response was overwhelming, with a total of 75 proposals submitted. Out of these, 27 were selected for seed…